Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database

Janet Sultana, Andrea Fontana, Francesco Giorgianni, Giorgio Basile, Elisabetta Patorno, Alberto Pilotto, Mariam Molokhia, Robert Stewart, Miriam Sturkenboom, Gianluca Trifirò

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people. Materials and methods: A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status. Results: A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95% confidence interval [CI]) increased from 0.71 (0.70–0.72) to 0.76 (0.75–0.77) and 0.73 (0.71–0.75) to 0.79 (0.77–0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia. Conclusion: Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded.

Original languageEnglish
Pages (from-to)31-39
Number of pages9
JournalClinical Epidemiology
Volume10
DOIs
Publication statusPublished - Jan 1 2018

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Independent Living
Primary Health Care
Cohort Studies
Databases
Mortality
Dementia
Cognition
Health
Bandages
General Practice
General Practitioners
Comorbidity
Logistic Models
Confidence Intervals

Keywords

  • Database
  • Elderly
  • Frailty
  • Mortality

ASJC Scopus subject areas

  • Epidemiology

Cite this

Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database. / Sultana, Janet; Fontana, Andrea; Giorgianni, Francesco; Basile, Giorgio; Patorno, Elisabetta; Pilotto, Alberto; Molokhia, Mariam; Stewart, Robert; Sturkenboom, Miriam; Trifirò, Gianluca.

In: Clinical Epidemiology, Vol. 10, 01.01.2018, p. 31-39.

Research output: Contribution to journalArticle

Sultana, J, Fontana, A, Giorgianni, F, Basile, G, Patorno, E, Pilotto, A, Molokhia, M, Stewart, R, Sturkenboom, M & Trifirò, G 2018, 'Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database', Clinical Epidemiology, vol. 10, pp. 31-39. https://doi.org/10.2147/CLEP.S145530
Sultana, Janet ; Fontana, Andrea ; Giorgianni, Francesco ; Basile, Giorgio ; Patorno, Elisabetta ; Pilotto, Alberto ; Molokhia, Mariam ; Stewart, Robert ; Sturkenboom, Miriam ; Trifirò, Gianluca. / Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database. In: Clinical Epidemiology. 2018 ; Vol. 10. pp. 31-39.
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abstract = "Background: Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people. Materials and methods: A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status. Results: A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95{\%} confidence interval [CI]) increased from 0.71 (0.70–0.72) to 0.76 (0.75–0.77) and 0.73 (0.71–0.75) to 0.79 (0.77–0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia. Conclusion: Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded.",
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AU - Basile, Giorgio

AU - Patorno, Elisabetta

AU - Pilotto, Alberto

AU - Molokhia, Mariam

AU - Stewart, Robert

AU - Sturkenboom, Miriam

AU - Trifirò, Gianluca

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N2 - Background: Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people. Materials and methods: A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status. Results: A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95% confidence interval [CI]) increased from 0.71 (0.70–0.72) to 0.76 (0.75–0.77) and 0.73 (0.71–0.75) to 0.79 (0.77–0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia. Conclusion: Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded.

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